Boeing warned on Saturday of layoffs in its Space Launch System moon rocket program, saying it expects to have about 400 fewer positions in line with revisions to NASA's Artemis program and cost expectations. "We are working with our customer and seeking opportunities to redeploy employees ...

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White House advisor Elon Musk has a new priority: the delivery of a pair of luxurious Boeing 747s, so he and Trump can jet around in style.

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Catch Yahoo Finance's interview with GM CEO Mary Barra, where she weighs in on President Trump's possible tariffs. Also on the earnings front, Boeing (BA) reported $4 billion in operating losses tied to its labor strikes that impacted the aircraft manufacturer.

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DUBLIN (Reuters) - Boeing expects to reach a balance between supply and market demand for passenger jets by the end of the decade, an executive said on Monday.

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In Belgium, a Boeing 737 jetliner quite literally fell flat on its nose — and the airline behind it is stumped as to what happened.

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As we have seen with Boeing Co. and others, ransomware—online extortion schemes perpetrated against vulnerable companies—remains a top concern. And OT and the vast supply chain...

Crystal Ball preview: Top cybersecurity risks in 2025 and beyond | Smart Industry

"X-37B missions have continuously advanced our nation's space capabilities by testing new technologies that reduce risk and inform our future space architectures," said program director for Boeing's Experimental Systems Group Holly Murphy in the video.

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Space-tracking company ExoAnalytic Solutions has identified a whopping 500 pieces of debris left over from an exploded Boeing satellite.

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As the Wall Street Journal reports, sources claim that Boeing is looking to get out of the space race by selling its Starliner business.

Boeing Reportedly Looking to Sell Off Its Disastrous Starliner Spacecraft

Boeing

boeing

Yaroslav Zubko has crafted a remarkable international career, creating designs for Boeing, Markit, Deloitte, and Tinder. His exceptional work has earned him prestigious accolades, including the DotComm Award and the Clio Awards, one of the oldest creative awards in the US. The latter was received for one of Tinder's most famous projects, Swipe Night. How did he achieve such impressive feats in the competitive world of design? From Law to Designs Zubko’s journey began in the heart of Ukraine, a burgeoning hub for IT and design. Initially, he studied business law at a local college but decided to follow his passion and started studying graphic design online. In 2012, he landed his first job as a web designer at a Ukrainian fitness retail company, Terrasport. That work, along with some other early projects, laid the foundation for his work philosophy, characterized by a harmonious blend of aesthetics and functionality. In 2017, he assumed the role of product design director at UpTop, a New York-based property management startup. There, he was in charge of choosing which product features to research and test and deciding how they would be implemented. “There were nights when I couldn't fall asleep because I was thinking about ideas for the product,” Zubko recalls. Concurrently, he dedicated his time to “Interaction Library,” an ambitious project he had been nurturing since 2016. The initiative aimed to curate a comprehensive collection of interaction samples and interface behaviors, serving as a valuable resource for designers and stakeholders. American Odyssey The library's publication on platforms like Dribbble not only earned Zubko industry recognition but also captured the attention of business leaders. Among them was Tinder's Jonathan Badeen, who extended an offer to the designer, marking the beginning of a new chapter in Zubko’s professional life as the lead product designer at the dating giant in 2018. Zubko was entrusted with reshaping Tinder's user experience, with a focus on monetization and engagement. “I animated and presented over 20 versions of Tinder's app, and used A/B testing methods to understand what ideas were worth implementing,” he recalls. One of the standout achievements during his tenure was the restyling of subscription packages in alignment with Apple Store guidelines. This initiative not only enhanced the user experience but also paved the way for sustainable revenue growth. Zubko’s ability to balance user-centric design and revenue optimization was a testament to his holistic approach to product design. He often noted that his goal was to align Tinder's business objectives with user needs, creating a win-win scenario for the company and its users. His original design solutions helped reinvigorate Tinder's premium offerings, catapulting the app's revenue to new heights. Learning Solutions Transitioning from the realm of dating apps to educational technology and leveraging his previous experience, Zubko launched Fluently in 2019—a mobile application dedicated to immersive language exchange. In 2020, he was commissioned by Riiid Labs, which builds AI-based personalized learning solutions. It is one of the major players in the EdTech field, backed by $250 million in investment funding. At the company, Zubko took on the role of director of product design, contributing to Riiid's mission of revolutionizing personalized learning through AI and gamification. Drawing from his insights into UX/UI design, user engagement, and gamification strategies, Zubko led several notable projects. For instance, he worked on an application that helped American students to prepare for the SAT, a standardized test widely used for college admissions in the United States. He also developed the mobile app DE Saber for Colombian students preparing for the Saber 11, a high school exit examination for college admission. Further, Zubko was invited to join Shiftsmart, a company that developed a platform assisting with team onboarding and training, performance management, scheduling and shift dispatch, and more. Shiftsmart raised a total of $117 million in funding, attracting prominent investment firms such as D1 Capital, Spieker Partners, Oakridge Management Group, and S12F, among others. Zubko served as a Senior Designer at the company and worked on the creation of the mobile app and branding. Towards Rewards Zubko’s original designs have earned prestigious international awards and industry acclaim. For instance, he was recognized as Designer of the Year 2019 by the Ukrainian IT Awards. He also won an international competition, the dotCOMM Awards, and the Italian A' Design Award for one of his freelance projects, FameLab. FameLab is a leading social marketing cloud that delivers authentic engagement on Instagram, Snapchat, and Facebook Pages. Zubko created interactive designs for the company’s app. He also contributed ideas and concepts to the Swipe Night initiative created for Tinder by the advertising agency 72andSunny in 2019. This was an interactive mini-series about friends trying to save themselves from the apocalypse. Users could participate in the series by swiping, thereby making decisions for the main characters. Based on users' choices, Tinder would then offer potential matches. In 2020, this project won a Clios, one of the oldest awards in the US, recognizing innovation and creative excellence in advertising, design, and communication. In 2021, Swipe Night was awarded the Entertainment Grand Prix at Cannes and was nominated for a Daytime Emmy Award for Interactive Media. Yaroslav Zubko has crafted a remarkable international career, creating designs for Boeing, Markit, Deloitte, and Tinder. His exceptional work has earned him prestigious accolades, including the DotComm Award and the Clio Awards, one of the oldest creative awards in the US. The latter was received for one of Tinder's most famous projects, Swipe Night. How did he achieve such impressive feats in the competitive world of design? From Law to Designs Zubko’s journey began in the heart of Ukraine, a burgeoning hub for IT and design. Initially, he studied business law at a local college but decided to follow his passion and started studying graphic design online. In 2012, he landed his first job as a web designer at a Ukrainian fitness retail company, Terrasport. That work, along with some other early projects, laid the foundation for his work philosophy, characterized by a harmonious blend of aesthetics and functionality. In 2017, he assumed the role of product design director at UpTop, a New York-based property management startup. There, he was in charge of choosing which product features to research and test and deciding how they would be implemented. “There were nights when I couldn't fall asleep because I was thinking about ideas for the product,” Zubko recalls. Concurrently, he dedicated his time to “ Interaction Library ,” an ambitious project he had been nurturing since 2016. The initiative aimed to curate a comprehensive collection of interaction samples and interface behaviors, serving as a valuable resource for designers and stakeholders. Interaction Library Interaction Library American Odyssey The library's publication on platforms like Dribbble not only earned Zubko industry recognition but also captured the attention of business leaders. Among them was Tinder's Jonathan Badeen, who extended an offer to the designer, marking the beginning of a new chapter in Zubko’s professional life as the lead product designer at the dating giant in 2018. Zubko was entrusted with reshaping Tinder's user experience, with a focus on monetization and engagement. “I animated and presented over 20 versions of Tinder's app, and used A/B testing methods to understand what ideas were worth implementing,” he recalls. One of the standout achievements during his tenure was the restyling of subscription packages in alignment with Apple Store guidelines. This initiative not only enhanced the user experience but also paved the way for sustainable revenue growth. Zubko’s ability to balance user-centric design and revenue optimization was a testament to his holistic approach to product design. He often noted that his goal was to align Tinder's business objectives with user needs, creating a win-win scenario for the company and its users. His original design solutions helped reinvigorate Tinder's premium offerings, catapulting the app's revenue to new heights. Learning Solutions Transitioning from the realm of dating apps to educational technology and leveraging his previous experience, Zubko launched Fluently in 2019—a mobile application dedicated to immersive language exchange. In 2020, he was commissioned by Riiid Labs, which builds AI-based personalized learning solutions. It is one of the major players in the EdTech field, backed by $250 million in investment funding. At the company, Zubko took on the role of director of product design, contributing to Riiid's mission of revolutionizing personalized learning through AI and gamification. Drawing from his insights into UX/UI design, user engagement, and gamification strategies, Zubko led several notable projects. For instance, he worked on an application that helped American students to prepare for the SAT, a standardized test widely used for college admissions in the United States. He also developed the mobile app DE Saber for Colombian students preparing for the Saber 11, a high school exit examination for college admission. Further, Zubko was invited to join Shiftsmart, a company that developed a platform assisting with team onboarding and training, performance management, scheduling and shift dispatch, and more. Shiftsmart raised a total of $117 million in funding, attracting prominent investment firms such as D1 Capital, Spieker Partners, Oakridge Management Group, and S12F, among others. Zubko served as a Senior Designer at the company and worked on the creation of the mobile app and branding. attracting attracting Towards Rewards Zubko’s original designs have earned prestigious international awards and industry acclaim. For instance, he was recognized as Designer of the Year 2019 by the Ukrainian IT Awards. He also won an international competition, the dotCOMM Awards, and the Italian A' Design Award for one of his freelance projects, FameLab. FameLab is a leading social marketing cloud that delivers authentic engagement on Instagram, Snapchat, and Facebook Pages. Zubko created interactive designs for the company’s app. He also contributed ideas and concepts to the Swipe Night initiative created for Tinder by the advertising agency 72andSunny in 2019. This was an interactive mini-series about friends trying to save themselves from the apocalypse. Users could participate in the series by swiping, thereby making decisions for the main characters. Based on users' choices, Tinder would then offer potential matches. In 2020, this project won a Clios, one of the oldest awards in the US, recognizing innovation and creative excellence in advertising, design, and communication. In 2021, Swipe Night was awarded the Entertainment Grand Prix at Cannes and was nominated for a Daytime Emmy Award for Interactive Media. won won awarded awarded

How a Designer Landed a Job at Tinder and Achieved International Recognition

Since the market crashed in March of 2020 the rebound has been swift and irrational. Boeing, for example, is in many ways worse off than it was in March. It’s clear air travel has plummeted and that airlines will be impacted for years. Where will airlines get the money to purchase planes? An example of one headline in April: . “Boeing customers cancel staggering 150 Max plane orders” Buy the dip? One thing I’ve noticed is that since the end of March you can basically just buy every dip and expect a pop, selling the next day. I mentioned this to a friend on Friday and decided to backtest it. Well, sure enough it works! I’ll mention I made one modification. Originally I wrote the system like so: 1. Check if Boeing is down more than 3% 15 minutes from close 2. If yes, buy with 100% of portfolio 3. The next day, 15 minutes from open liquidate the portfolio. This worked OK. Great actually! It returned about . But want to know what really kicked it up a notch? 25% Instead of just selling the next day, I only sell if the position is sitting at a realized gain. So e.g. if the next day its flat or drops another 1%, don’t sell it, just keep holding on until its up and THEN sell. Of course, this is completely insane and you would have to expect the market to only go up, but that’s what has been happening. Guess what? This simple system . Yeah, I know, crazy. returned a whopping 65% in two-ish months Check out the backtest screenshot: And here are the raw trading logs for those that want to see the dates the trades were made: Here is the code! Before we look at the code, I'll just mention here are the details of the backtest: - start with 100k in cash - start at April first and go until last Friday (June 19th 2020) - end up with about 165k or a 65% return. I wrote this little script on Quant Connect. The screenshot at the top of the page is the backtest result, and the code below is everything you need to try this out. Note the place I mentioned in the code you should comment if you want this to be a little bit less insane. self.SetStartDate( , , ) self.SetEndDate( , , ) self.SetCash( ) self.SetWarmUp( )
        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage)

        self.AddEquity( , Resolution.Minute)
        self.SetBenchmark( )

        self.targetSymbol = self.openPrice = self.downPctTrigger = self.AddEquity(self.targetSymbol, Resolution.Minute, Market.USA, , )

        self.Schedule.On(self.DateRules.EveryDay(self.targetSymbol), self.TimeRules.AfterMarketOpen(self.targetSymbol, ), Action(self.onMarketOpen))
        self.Schedule.On(self.DateRules.EveryDay(self.targetSymbol), self.TimeRules.AfterMarketOpen(self.targetSymbol, ), Action(self.sellItIfHeld))
        self.Schedule.On(self.DateRules.EveryDay(self.targetSymbol), self.TimeRules.BeforeMarketClose(self.targetSymbol, ), Action(self.buyIfDown)) self.openPrice = self.Securities[self.targetSymbol].Open currPrice = self.Securities[self.targetSymbol].Price
        openPrice = self.openPrice pctDiff = (currPrice - openPrice) / openPrice pctDiff < self.downPctTrigger:
            self.Debug( + str(currPrice) + + str(pctDiff))
            self.SetHoldings(self.targetSymbol, ) self.Portfolio[self.targetSymbol].Quantity > : self.Portfolio[self.targetSymbol].UnrealizedProfit < : currPrice = self.Securities[self.targetSymbol].Price
            self.Debug( + str(currPrice))
            self.Liquidate(self.targetSymbol) : class BasicTemplateAlgorithm (QCAlgorithm) : def Initialize (self) 2020 4 1 #Set Start Date 2020 6 12 #Set End Date 100000 #Set Strategy Cash 0 "SPY" "SPY" "BA" 0 -0.03 True 1.0 1 15 15 : def OnData (self, data) pass : def onMarketOpen (self) : def buyIfDown (self) # e.g. (95 - 100) / 100 = -0.05 # if gt than loss of x if "Buying at: " " pct down: " 1.0 : def sellItIfHeld (self) if 0 # just making this easy to comment out # this is the logic that says only sell if you are sitting on a profit # otherwise, we just keep holding until the price moves up if 0 return "Selling at: " Obligatory warning and disclaimer Try the backtest yourself. And, by the way, I’m just talking about the backtest. This is not investment advice, nor am I suggesting you actually do this. Nothing in this article constitutes professional investment advice. Please do your own research before making and investment decisions. running There are obvious risks with this, e.g. one day Boeing could just declare bankruptcy and the price goes down and never recovers. This is for informational purposes only. And of course, feel free to shoot me an email if want to talk about trading or algorithm ideas!

How I Made a 65% ROI with this Boeing Trading Algorithm

Analyzing the Impact of Model Scaling on Long-Form Factuality

Hedera (HBAR) has long positioned itself as a leading blockchain for institutional adoption, thanks to its governance council model featuring companies like Google, IBM, and Boeing. While this structure offers stability and enterprise credibility, it has also raised concerns about decentralization, with critics arguing that decision-making is concentrated in the hands of corporate giants. In contrast, Coldware’s Web3-native approach is attracting investors who prioritize decentralization and open governance. Coldware is designed to be fully community-driven, enabling token holders to actively shape the network’s development and governance policies. As a result, HBAR whales are beginning to shift toward Coldware (COLD), recognizing its long-term potential in DePIN and PayFi applications. Hedera (HBAR) recently saw a 10.9% surge following news of a partnership with Snoop Dogg’s Tune.fm, reinforcing Hedera’s position in the Web3 music and entertainment space. However, institutional investors are looking beyond entertainment applications, with DePIN and PayFi emerging as key sectors for blockchain adoption. Coldware (COLD) is positioning itself as the go-to blockchain for real-world infrastructure and decentralized finance, making it a compelling alternative for HBAR investors. With Coldware’s presale already surpassing $1.25M, the momentum is shifting toward next-generation blockchains that offer greater flexibility, scalability, and decentralization. Hedera’s Centralized Council vs. Coldware’s Decentralized Network \One of the biggest criticisms of Hedera is its governing council, which limits community participation in decision-making. While this model is ideal for large-scale enterprise adoption, it contradicts the decentralized ethos of blockchain technology. Coldware (COLD), on the other hand, empowers its community, ensuring that protocol upgrades, network governance, and staking rewards are controlled by token holders rather than corporate entities. This fully decentralized model is attracting Web3 investors and institutional players who value transparency and community governance. Coldware’s PayFi Model Challenges HBAR’s Institutional Focus \Hedera’s (HBAR) focus on enterprise partnerships has helped it gain credibility among traditional financial institutions. However, Coldware’s PayFi model offers a more inclusive, community-driven alternative that appeals to both institutions and retail users. By facilitating fast, low-cost transactions for businesses and individuals, Coldware is setting itself apart as a blockchain that prioritizes both financial inclusion and institutional-grade security. This dual focus is why HBAR whales are increasingly backing Coldware’s presale, seeing it as a long-term investment opportunity in the growing PayFi sector. Will Coldware Become the Next Institutional-Grade Blockchain? While Hedera (HBAR) remains a strong player in blockchain infrastructure, its corporate-heavy governance model may limit its Web3 adoption potential. Coldware (COLD), with its community-first approach and focus on DePIN and PayFi, is positioning itself as a true alternative for institutions looking for decentralized financial solutions.\ With Coldware’s presale continuing to gain traction, it’s clear that HBAR investors are taking notice. As the battle between centralized and decentralized governance models unfolds, Coldware’s Web3 approach is quickly gaining momentum—proving that blockchain’s future lies in decentralization, not corporate control. For more information on the Coldware (COLD) Presale: Visit Coldware (COLD) Join and become a community member: https://t.me/coldwarenetwork https://x.com/ColdwareNetwork This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. Hedera (HBAR) has long positioned itself as a leading blockchain for institutional adoption, thanks to its governance council model featuring companies like Google, IBM, and Boeing. While this structure offers stability and enterprise credibility, it has also raised concerns about decentralization, with critics arguing that decision-making is concentrated in the hands of corporate giants. In contrast, Coldware’s Web3-native approach is attracting investors who prioritize decentralization and open governance. Coldware is designed to be fully community-driven, enabling token holders to actively shape the network’s development and governance policies. As a result, HBAR whales are beginning to shift toward Coldware (COLD) , recognizing its long-term potential in DePIN and PayFi applications. Coldware (COLD) Coldware (COLD) Hedera (HBAR) recently saw a 10.9% surge following news of a partnership with Snoop Dogg’s Tune.fm, reinforcing Hedera’s position in the Web3 music and entertainment space. However, institutional investors are looking beyond entertainment applications, with DePIN and PayFi emerging as key sectors for blockchain adoption. Coldware (COLD) is positioning itself as the go-to blockchain for real-world infrastructure and decentralized finance, making it a compelling alternative for HBAR investors. With Coldware’s presale already surpassing $1.25M, the momentum is shifting toward next-generation blockchains that offer greater flexibility, scalability, and decentralization. Coldware (COLD) Coldware (COLD) Hedera’s Centralized Council vs. Coldware’s Decentralized Network \One of the biggest criticisms of Hedera is its governing council, which limits community participation in decision-making. While this model is ideal for large-scale enterprise adoption, it contradicts the decentralized ethos of blockchain technology. Coldware (COLD) , on the other hand, empowers its community, ensuring that protocol upgrades, network governance, and staking rewards are controlled by token holders rather than corporate entities. This fully decentralized model is attracting Web3 investors and institutional players who value transparency and community governance. Coldware (COLD) Coldware (COLD) Coldware’s PayFi Model Challenges HBAR’s Institutional Focus \Hedera’s (HBAR) focus on enterprise partnerships has helped it gain credibility among traditional financial institutions. However, Coldware’s PayFi model offers a more inclusive, community-driven alternative that appeals to both institutions and retail users. By facilitating fast, low-cost transactions for businesses and individuals, Coldware is setting itself apart as a blockchain that prioritizes both financial inclusion and institutional-grade security. This dual focus is why HBAR whales are increasingly backing Coldware’s presale, seeing it as a long-term investment opportunity in the growing PayFi sector. Will Coldware Become the Next Institutional-Grade Blockchain? While Hedera (HBAR) remains a strong player in blockchain infrastructure, its corporate-heavy governance model may limit its Web3 adoption potential. Coldware (COLD) , with its community-first approach and focus on DePIN and PayFi, is positioning itself as a true alternative for institutions looking for decentralized financial solutions.\ Coldware (COLD) Coldware (COLD) With Coldware’s presale continuing to gain traction, it’s clear that HBAR investors are taking notice. As the battle between centralized and decentralized governance models unfolds, Coldware’s Web3 approach is quickly gaining momentum—proving that blockchain’s future lies in decentralization, not corporate control. For more information on the Coldware (COLD) Presale: Visit Coldware (COLD) Coldware (COLD) Coldware (COLD) Join and become a community member: https://t.me/coldwarenetwork https://t.me/coldwarenetwork https://t.me/coldwarenetwork https://x.com/ColdwareNetwork https://x.com/ColdwareNetwork https://x.com/ColdwareNetwork This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. This article is published under HackerNoon’s Business Blogging program. Do your own research before making any financial decisions. Business Blogging Business Blogging

DePIN and PayFi: Coldware’s Web3 Community Approach

DePIN እና PayFi፡ Coldware Web3 Community Approach

DePIN i PayFi: Coldwareov Web3 pristup zajednici

DePIN und PayFi: Coldwares Web3-Community-Ansatz

DePIN y PayFi: el enfoque comunitario Web3 de Coldware

DePIN ja PayFi: Coldwaren Web3 Community Approach

DePIN と PayFi: Coldware の Web3 コミュニティ アプローチ

DePIN និង PayFi៖ វិធីសាស្រ្តសហគមន៍ Web3 របស់ Coldware

DePIN 및 PayFi: Coldware의 Web3 커뮤니티 접근 방식

DePIN e PayFi: Abordagem da Comunidade Web3 da Coldware

DePIN и PayFi: подход Coldware к сообществу Web3

DePIN na PayFi: Uburyo bwa Coldware's Web3 Uburyo bwabaturage

DePIN va PayFi: sovuq dasturiy ta'minotning Web3 hamjamiyatiga yondashuvi

When ChatGPT was first released publicly (2 years ago), I had the same reaction as most people. First excitement, then a wave of fear. I mean, artificial intelligence wasn’t new to me; it was one of my core subjects while studying for my degree in Computer science, and I had even written a paper on the application of AI in Nanomedicine. However, what was new to me was how quickly and easily we got AI tools that were ready for mass adoption. It was clear that the world was going to change very quickly, and I had to understand what it meant for the future of tech. To understand this change, I looked back to times in history when we experienced similar leaps in technology to see what I could learn from it. I went back to research the work of tech pioneers like Alan Turing. I went back to research the rise of the Industrial Revolution and visited a few museums dedicated to this period. I’ve closely observed how people use AI today. If the advancement of AI continues at the current rate, then this is how I believe it will change how we build software products. 1. The End of ‘Busy Work.’ The first thing AI will put an end to is ‘busy work’. I describe ‘busy work’ as those activities that are part of most jobs but don’t have any real value. For example, a product manager’s job often involves writing user stories/tickets, while an engineer’s often involves setting up their dev environment. These things make you feel like you’re working but are usually a poor use of your time or skills. This will come to an end. AI will shift the value of work from mundane tasks to focusing on what truly matters. This happened a lot during the Industrial Revolution. For example, before the automated flour mill was invented, you needed a lot of people to do repetitive tasks like pouring grain, but after the invention, there was a focus on speed, quality control, and the taste of the flour. It is already happening with AI and software today, but I predict a future where things like writing tickets or setting up dev environments by yourself will only happen on very special occasions. Any tech worker who hasn’t yet understood where the true value of their role lies needs to figure it out now. PS: It’s not writing user stories 2. Distribution Will Become More Important Than Ever. When massive railway expansions started during the Industrial Revolution, it greatly benefited those who were able to take advantage of it. Businesses that were able to strike good deals with the railway corporation(s) were able to outcompete others due to cost-effective distribution. By distribution here, I mean how you get your goods and services in front of your customers. Even looking back to the Roman Empire, controlling trade routes like the Mediterranean was an important aspect of distribution. However, in modern times, knowing how to use Facebook ads efficiently or having a large audience on social media is how distribution works. Distribution has always been important. As it becomes easier to build software using AI, distribution will become more important than ever. This is because it will become relatively cheap to make or copy software products, so the more important thing will be how to get those products into the hands of customers. Everyone will be able to make software but not everyone will know how to get them in front of customers efficiently. Do you have a large following online? Do you have a strong professional or personal network? Are you part of any communities that could give you a unique advantage? Do you know how to run effective ad campaigns? You need to figure out what your distribution advantage will be if you intend to remain in the business of making software. 3. Software Will Become Very Personal. Before the sewing machine was invented, most people had 2 sets of clothing; one for work and the other for special occasions (Sunday best). There was also very little style or customization available for most people because it took so much time and manual effort to make the clothes you had in the first place. When the sewing machine was invented during the Industrial Revolution, it changed how people dressed. For the first time, the masses could access a wide variety of clothes and choose how they wanted to dress based on their style or personal needs. I believe AI will do the same for software. My experience in the software industry has shown me that most software users only care about the outcome they want and the tools they need to get that specific outcome. Most users don’t care about other features of the platform or how other people use it; they only care about their use case and often disregard every other thing. This is even clear in the evolution of the SaaS industry. The first generation of SaaS platforms (e.g., SAP, Salesforce) attempted to do everything. Then we had the phase of unbundling where businesses picked one use case of a particular general-purpose software and focused on that use case (e.g., Hubspot CRM). Then we moved into vertical SaaS where a lot of platforms focused on one business vertical or industry e.g., CRMs for Medical practitioners. More recently, we have moved into the micro-SaaS era, where there are platforms that are so niche that they sometimes do only 1 thing, but do it really well. Software is getting more personal and my prediction is that people/businesses will start to ‘generate’ software that helps them achieve a specific goal that they have. Think about it. Why do I have to pay for a tool that has 20 features when I only ever use 7? And of those 7 features only 80% of my use case is covered exactly how I want… AI will change this. Small teams and departments in organizations will start using AI to ‘generate’ software to solve specific problems or achieve specific goals that they have. 4. Taste Will Become More Important. I describe having good taste as having a strong sense of what good, bad, or great looks like. It was the difference between Apple and Blackberry in the early days of the iPhone, even though both companies had large amounts of money in the bank. The difference between Boeing Space and Spacex… and what could be the difference between the winners and losers in this AI-led software development era? Since building software will become relatively cheap, having a strong taste will become very important in the software business. In the past, you could get away with building poorly thought-out software but you won’t be able to get away with it anymore. My prediction is that there will be less emphasis on how to build from a technical point of view and more focus on deciding what to build and how it should work. There will also be more emphasis on why it should be built. People with great taste in software will be the winners in this new AI world. Start developing your taste today. Start developing a clear sense of what good, bad, and great software feels like. It will give you the ultimate edge. Thanks for taking the time to read this. Please let me know if you think I’ve missed any strong themes on how software products will change in this new reality. Thanks to my friend Faith for editing this! When ChatGPT was first released publicly (2 years ago), I had the same reaction as most people. First excitement, then a wave of fear. I mean, artificial intelligence wasn’t new to me; it was one of my core subjects while studying for my degree in Computer science, and I had even written a paper on the application of AI in Nanomedicine . Nanomedicine However, what was new to me was how quickly and easily we got AI tools that were ready for mass adoption. It was clear that the world was going to change very quickly, and I had to understand what it meant for the future of tech. To understand this change, I looked back to times in history when we experienced similar leaps in technology to see what I could learn from it. I went back to research the work of tech pioneers like Alan Turing . Alan Turing I went back to research the rise of the Industrial Revolution and visited a few museums dedicated to this period. Industrial Revolution I’ve closely observed how people use AI today. If the advancement of AI continues at the current rate, then this is how I believe it will change how we build software products. 1. The End of ‘Busy Work.’ The first thing AI will put an end to is ‘busy work’. I describe ‘busy work’ as those activities that are part of most jobs but don’t have any real value. For example, a product manager’s job often involves writing user stories/tickets, while an engineer’s often involves setting up their dev environment. These things make you feel like you’re working but are usually a poor use of your time or skills. This will come to an end. AI will shift the value of work from mundane tasks to focusing on what truly matters. This happened a lot during the Industrial Revolution. For example, before the automated flour mill was invented, you needed a lot of people to do repetitive tasks like pouring grain, but after the invention, there was a focus on speed, quality control, and the taste of the flour. It is already happening with AI and software today, but I predict a future where things like writing tickets or setting up dev environments by yourself will only happen on very special occasions. Any tech worker who hasn’t yet understood where the true value of their role lies needs to figure it out now. PS : It’s not writing user stories PS 2. Distribution Will Become More Important Than Ever. When massive railway expansions started during the Industrial Revolution, it greatly benefited those who were able to take advantage of it. Businesses that were able to strike good deals with the railway corporation(s) were able to outcompete others due to cost-effective distribution. By distribution here, I mean how you get your goods and services in front of your customers. Even looking back to the Roman Empire, controlling trade routes like the Mediterranean was an important aspect of distribution. However, in modern times, knowing how to use Facebook ads efficiently or having a large audience on social media is how distribution works. Distribution has always been important. As it becomes easier to build software using AI, distribution will become more important than ever. This is because it will become relatively cheap to make or copy software products, so the more important thing will be how to get those products into the hands of customers. Everyone will be able to make software but not everyone will know how to get them in front of customers efficiently. Do you have a large following online? Do you have a strong professional or personal network? Are you part of any communities that could give you a unique advantage? Do you know how to run effective ad campaigns? You need to figure out what your distribution advantage will be if you intend to remain in the business of making software. 3. Software Will Become Very Personal. Before the sewing machine was invented, most people had 2 sets of clothing; one for work and the other for special occasions (Sunday best). There was also very little style or customization available for most people because it took so much time and manual effort to make the clothes you had in the first place. When the sewing machine was invented during the Industrial Revolution, it changed how people dressed. For the first time, the masses could access a wide variety of clothes and choose how they wanted to dress based on their style or personal needs. I believe AI will do the same for software. My experience in the software industry has shown me that most software users only care about the outcome they want and the tools they need to get that specific outcome. Most users don’t care about other features of the platform or how other people use it; they only care about their use case and often disregard every other thing. This is even clear in the evolution of the SaaS industry. The first generation of SaaS platforms (e.g., SAP, Salesforce) attempted to do everything. Then we had the phase of unbundling where businesses picked one use case of a particular general-purpose software and focused on that use case (e.g., Hubspot CRM). unbundling Then we moved into vertical SaaS where a lot of platforms focused on one business vertical or industry e.g., CRMs for Medical practitioners. More recently, we have moved into the micro-SaaS era, where there are platforms that are so niche that they sometimes do only 1 thing, but do it really well. micro-SaaS Software is getting more personal and my prediction is that people/businesses will start to ‘ generate ’ software that helps them achieve a specific goal that they have. generate Think about it. Why do I have to pay for a tool that has 20 features when I only ever use 7? And of those 7 features only 80% of my use case is covered exactly how I want… AI will change this. Small teams and departments in organizations will start using AI to ‘ generate ’ software to solve specific problems or achieve specific goals that they have. generate 4. Taste Will Become More Important. I describe having good taste as having a strong sense of what good, bad, or great looks like. strong It was the difference between Apple and Blackberry in the early days of the iPhone, even though both companies had large amounts of money in the bank. The difference between Boeing Space and Spacex … Boeing Space Spacex and what could be the difference between the winners and losers in this AI-led software development era? Since building software will become relatively cheap, having a strong taste will become very important in the software business. In the past, you could get away with building poorly thought-out software but you won’t be able to get away with it anymore. My prediction is that there will be less emphasis on how to build from a technical point of view and more focus on deciding what to build and how it should work . how to build what to build how it should work There will also be more emphasis on why it should be built . why it should be built People with great taste in software will be the winners in this new AI world. Start developing your taste today. Start developing a clear sense of what good, bad, and great software feels like. It will give you the ultimate edge. Thanks for taking the time to read this. Please let me know if you think I’ve missed any strong themes on how software products will change in this new reality. Thanks to my friend Faith for editing this!

Here's 4 Ways AI Will Change Software: Plus, What The Industrial Revolution Taught Me About It

Agile Is Rigor Mortis as Software’s State Religion

Agile is Rigor Mortis as sagteware se staatsgodsdiens

Agile es el rigor mortis como religión estatal del software

Agile da Rigor Mortis Softwarearen Estatuko Erlijio gisa

Agile est la Rigor Mortis comme religion d’État du logiciel

Agile Is Rigor Mortis כדת המדינה של תוכנה

Agile se Rigor Mortis kòm relijyon leta lojisyèl

アジャイルはソフトウェアの国教としての死後硬直である

Agile Adalah Rigor Mortis sebagai Agama Negeri Perisian

Agile é o rigor mortis como religião de estado do software

Ágil Rigor Mortis Softwarepa Estado Religionnin hina

Agile Is Rigor Mortis bilang Relihiyon ng Estado ng Software

I-Agile Is Rigor Mortis njengeNkolo Yezwe Yesoftware

The Geeks of War: How Dzyga's Paw Innovated Ukraine's Drone Operations

Introducing Yet Another Umpteenth Programming Language Yikes, gadzooks, and shiver me timbers! Yet another "new" programming language? Yes, Virginia, another new programming language. ZeptoN. Overview So, what the do-while is ZeptoN? Simple, ZeptoN is a simple programming language designed with two objectives... Simple learning language with common syntax style and structure.


A programming language for quick-and-dirty “throwaway programs.” My Programming History As a young boy and a teenager, I cut my teeth learning to program several programming languages. The first was the infamous and ubiquitous BASIC, and the other was Pascal. This was the 1980s, and the home computer revolution was underway. I describe how I got into software here xxx, and getting into programming led me to become a senior software engineer. Yet, one key feature of BASIC and Pascal was simplicity. Perhaps too simple in some ways, but the simplicity allowed the newbie or “noob” coder to start writing, running, and tinkering with code. I had subscriptions to “COMPUTE!” and bought programming books when I went to the mall. Yet, I could type in a program, run the code, and often, play computer games. BASIC Text Adventure I went so far as to write my own “electronic novel” which was a shameless imitation of some of the popular text adventures from Infocom, Adventure International. Mine was a murder mystery that “borrowed” from some other games, including the role-playing ones from companies like SirTech. The games were first written in BASIC, ultimately reaching GW-BASIC, and later in Turbo Pascal. This was more for the fun of creating and to impress friends to see if they could find the clues and solve the mystery. From this fascination with text adventures, I learned compiler theory concepts like lexical analysis, syntax, parsing, BNF, etc. Keep It Simple Silly Yet, there was the simplicity of BASIC and Pascal. Both programming languages were simple enough to teach important programming concepts, and often not formally. Then both programming languages were powerful enough and expressive enough to do neat and cool things, like my own text adventure. Now, when I look at introductory programming courses, powerful programming languages are often used--like Java, C++, and so forth. Great that mainstream languages are utilized that are in demand; there is only one small problem: Java, C++, C#, and Swift languages are very complex as they use the object-oriented paradigm. For a noob or newb, for a newbie coder, that is a challenging and often frustrating language to learn. I initially experienced that at university, when the computer science department switched from a Pascal curriculum to a C++ one. The big frustration was going from a structured to an object-oriented paradigm. Learn to Fly With a Jetliner The simile I use is using Java/C++/C#/Swift/etc. is like learning to fly a plane by learning to pilot a Boeing 747 or an Airbus A330. A powerful aircraft, but overloading in terms of features, controls, and operation. Kernighan [Kerni 1981] even wrote that “Comparing C and Pascal is rather like comparing a Learjet to a Piper Cub — one is meant for getting something done while the other is meant for learning.” Yet, in this case, ZeptoN is meant for learning. ZeptoN has C/C++/Java syntax, so the most ubiquitous syntax style is used and is familiar, and ZeptoN transpiles or transcompiles from ZeptoN into Java. Thus, ZeptoN leverages Java ubiquity and platform neutrality. Hence, a newb can code ZeptoN on the MacOS, Linux, or Windows platforms. Back To BASIC One problem with BASIC (and to a lesser degree Pascal) was that each platform/computer--Atari 800, Commodore 64, IBM PC, Tandy 1000EX had its own “flavor” of BASIC. Thus, one BASIC program for the TI99/4A was not quite compatible with the TRS-80 BASIC, etc. I often found myself “adapting” BASIC programs to the computer I had at the time. ZeptoN avoids this by using Java, and having a standard environment of 70+ functions and several standard constants so ZeptoN can run anywhere. All ZeptoN requires is a favorite JDK vendor, with a minimum of JDK 11 for the transcompiler or code editor, Zeptor. Moreover, ZeptoN is free (yes as in free beer) and open-sourced using the GNU GPL v3. Hence, no cost and no proprietary or secret “black box” tool to transpile ZeptoN programs into Java .class bytecode. Testing Ideas With Throwaway Programs As a senior software engineer with 30+ years of writing code, I do like to write “test” programs to try something, and then throw them away. ZeptoN’s simplicity makes this possible, so for an advanced coder to the noob coder, ZeptoN is for everyone! For more details and examples check out the ZeptoN programming language white paper, a 49-page PDF or ePub document, for more details, and some samples of ZeptoN programs. Further Reading For more details and examples check out the ZeptoN programming language white paper and some samples of ZeptoN programs. More about ZeptoN here: https://github.com/wgilreath/ZeptoN and on my home site: https://www.wfgilreath.xyz/ Also the code editor Zeptor: https://github.com/wgilreath/Zeptor Here's ZeptoN in action and in use on Zeptor on YouTube! Enjoy the zither music... 😉 More articles to follow... 😜 about ZeptoN and Zeptor. Zept to it! References [Kerni 1981] Kernighan, Brian W. "Why Pascal is Not My Favorite Programming Language,"
Computing Science Technical Report No. 100, AT&T Bell Laboratories,
April 2, 1981.
https://www.lysator.liu.se/c/bwk-on-pascal.html
https://archive.org/details/pascal-not-my-favorite/page/n2/mode/1up


[Gilre 2024] Gilreath, William F. "Begin at the Beginning...My Start in Software Engineering," PDF (60K) https://bit.ly/will_soft_start


[Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," ePub (5.7Mb) https://wgilreath.github.io/ZeptonWhitePaper.epub


[Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," PDF (5.yMb) https://wgilreath.github.io/ZeptonWhitePaper.pdf Introducing Yet Another Umpteenth Programming Language Yikes, gadzooks, and shiver me timbers! Yet another "new" programming language? Yes, Virginia, another new programming language. ZeptoN. Overview So, what the do-while is ZeptoN? Simple, ZeptoN is a simple programming language designed with two objectives... Simple learning language with common syntax style and structure. A programming language for quick-and-dirty “throwaway programs.” Simple learning language with common syntax style and structure. Simple learning language with common syntax style and structure. A programming language for quick-and-dirty “throwaway programs.” A programming language for quick-and-dirty “throwaway programs.” My Programming History As a young boy and a teenager, I cut my teeth learning to program several programming languages. The first was the infamous and ubiquitous BASIC, and the other was Pascal. This was the 1980s, and the home computer revolution was underway. I describe how I got into software here xxx, and getting into programming led me to become a senior software engineer. Yet, one key feature of BASIC and Pascal was simplicity. Perhaps too simple in some ways, but the simplicity allowed the newbie or “noob” coder to start writing, running, and tinkering with code. I had subscriptions to “COMPUTE!” and bought programming books when I went to the mall. Yet, I could type in a program, run the code, and often, play computer games. BASIC Text Adventure I went so far as to write my own “electronic novel” which was a shameless imitation of some of the popular text adventures from Infocom, Adventure International. Mine was a murder mystery that “borrowed” from some other games, including the role-playing ones from companies like SirTech. The games were first written in BASIC, ultimately reaching GW-BASIC, and later in Turbo Pascal. This was more for the fun of creating and to impress friends to see if they could find the clues and solve the mystery. From this fascination with text adventures, I learned compiler theory concepts like lexical analysis, syntax, parsing, BNF, etc. Keep It Simple Silly Yet, there was the simplicity of BASIC and Pascal. Both programming languages were simple enough to teach important programming concepts, and often not formally. Then both programming languages were powerful enough and expressive enough to do neat and cool things, like my own text adventure. Now, when I look at introductory programming courses, powerful programming languages are often used--like Java, C++, and so forth. Great that mainstream languages are utilized that are in demand; there is only one small problem: Java, C++, C#, and Swift languages are very complex as they use the object-oriented paradigm. For a noob or newb, for a newbie coder, that is a challenging and often frustrating language to learn. I initially experienced that at university, when the computer science department switched from a Pascal curriculum to a C++ one. The big frustration was going from a structured to an object-oriented paradigm. Learn to Fly With a Jetliner The simile I use is using Java/C++/C#/Swift/etc. is like learning to fly a plane by learning to pilot a Boeing 747 or an Airbus A330. A powerful aircraft, but overloading in terms of features, controls, and operation. Kernighan [Kerni 1981] even wrote that “Comparing C and Pascal is rather like comparing a Learjet to a Piper Cub — one is meant for getting something done while the other is meant for learning.” Yet, in this case, ZeptoN is meant for learning. ZeptoN has C/C++/Java syntax, so the most ubiquitous syntax style is used and is familiar, and ZeptoN transpiles or transcompiles from ZeptoN into Java. Thus, ZeptoN leverages Java ubiquity and platform neutrality. Hence, a newb can code ZeptoN on the MacOS, Linux, or Windows platforms. Back To BASIC One problem with BASIC (and to a lesser degree Pascal) was that each platform/computer--Atari 800, Commodore 64, IBM PC, Tandy 1000EX had its own “flavor” of BASIC. Thus, one BASIC program for the TI99/4A was not quite compatible with the TRS-80 BASIC, etc. I often found myself “adapting” BASIC programs to the computer I had at the time. ZeptoN avoids this by using Java, and having a standard environment of 70+ functions and several standard constants so ZeptoN can run anywhere. All ZeptoN requires is a favorite JDK vendor, with a minimum of JDK 11 for the transcompiler or code editor, Zeptor. Moreover, ZeptoN is free (yes as in free beer) and open-sourced using the GNU GPL v3. Hence, no cost and no proprietary or secret “black box” tool to transpile ZeptoN programs into Java .class bytecode. Testing Ideas With Throwaway Programs As a senior software engineer with 30+ years of writing code, I do like to write “test” programs to try something, and then throw them away. ZeptoN’s simplicity makes this possible, so for an advanced coder to the noob coder, ZeptoN is for everyone! For more details and examples check out the ZeptoN programming language white paper, a 49-page PDF or ePub document, for more details, and some samples of ZeptoN programs. Further Reading For more details and examples check out the ZeptoN programming language white paper and some samples of ZeptoN programs. More about ZeptoN here: https://github.com/wgilreath/ZeptoN and on my home site: https://www.wfgilreath.xyz/ Also the code editor Zeptor: https://github.com/wgilreath/Zeptor https://github.com/wgilreath/ZeptoN https://www.wfgilreath.xyz/ https://github.com/wgilreath/Zeptor Here's ZeptoN in action and in use on Zeptor on YouTube ! Enjoy the zither music... 😉 YouTube More articles to follow... 😜 about ZeptoN and Zeptor. Zept to it! References [Kerni 1981] Kernighan, Brian W. "Why Pascal is Not My Favorite Programming Language,"
Computing Science Technical Report No. 100, AT&T Bell Laboratories,
April 2, 1981.
https://www.lysator.liu.se/c/bwk-on-pascal.html
https://archive.org/details/pascal-not-my-favorite/page/n2/mode/1up [Gilre 2024] Gilreath, William F. "Begin at the Beginning...My Start in Software Engineering," PDF (60K) https://bit.ly/will_soft_start [Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," ePub (5.7Mb) https://wgilreath.github.io/ZeptonWhitePaper.epub [Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," PDF (5.yMb) https://wgilreath.github.io/ZeptonWhitePaper.pdf [Kerni 1981] Kernighan, Brian W. "Why Pascal is Not My Favorite Programming Language,"
Computing Science Technical Report No. 100, AT&T Bell Laboratories,
April 2, 1981.
https://www.lysator.liu.se/c/bwk-on-pascal.html
https://archive.org/details/pascal-not-my-favorite/page/n2/mode/1up [Kerni 1981] Kernighan, Brian W. "Why Pascal is Not My Favorite Programming Language,"
Computing Science Technical Report No. 100, AT&T Bell Laboratories,
April 2, 1981. https://www.lysator.liu.se/c/bwk-on-pascal.html https://archive.org/details/pascal-not-my-favorite/page/n2/mode/1up https://www.lysator.liu.se/c/bwk-on-pascal.html https://archive.org/details/pascal-not-my-favorite/page/n2/mode/1up [Gilre 2024] Gilreath, William F. "Begin at the Beginning...My Start in Software Engineering," PDF (60K) https://bit.ly/will_soft_start [Gilre 2024] Gilreath, William F. "Begin at the Beginning...My Start in Software Engineering," PDF (60K) https://bit.ly/will_soft_start https://bit.ly/will_soft_start [Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," ePub (5.7Mb) https://wgilreath.github.io/ZeptonWhitePaper.epub [Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," ePub (5.7Mb) https://wgilreath.github.io/ZeptonWhitePaper.epub https://wgilreath.github.io/ZeptonWhitePaper.epub [Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," PDF (5.yMb) https://wgilreath.github.io/ZeptonWhitePaper.pdf [Gilre 2022] Gilre 2022, Gilreath, William F. "ZeptoN Programming Language," PDF (5.yMb) https://wgilreath.github.io/ZeptonWhitePaper.pdf https://wgilreath.github.io/ZeptonWhitePaper.pdf

What the Do-While Is ZeptoN?

Are We Morally Obligated to Adopt AI?

আমরা কি নৈতিকভাবে এআই গ্রহণ করতে বাধ্য?

Sind wir moralisch verpflichtet, KI einzuführen?

¿Estamos moralmente obligados a adoptar la IA?

Sommes-nous moralement obligés d’adopter l’IA ?

क्या हम नैतिक रूप से एआई को अपनाने के लिए बाध्य हैं?

私たちには AI を導入する道徳的義務があるのでしょうか?

우리는 AI를 채택해야 할 도덕적 의무가 있습니까?

Somos moralmente obrigados a adotar a IA?

Обязаны ли мы морально принять ИИ?

Ahlaki Olarak Yapay Zekayı Benimsetmek Zorunda mıyız?

Chúng ta có nghĩa vụ về mặt đạo đức phải áp dụng AI?

我们在道义上有义务采用人工智能吗？

Yuan Yi Zhu, an Assistant Professor of International Relations and International Law at Leiden University, recently criticized an article published in The Times of London. The article was written by Matthew Parris, a former Member of the British Parliament. In the article, Parris argues in favor of legalizing euthanasia on the grounds that society simply cannot afford “desperate infirmity for as many such individuals as our society is producing.” Parris argues that it would allow the UK economy to better compete with China and people being coerced to being euthanised due to social pressure is “not a bad thing”. Parris says he does not apologise for how his article "treats human beings as units - in deficit or surplus to the collective". In February 2024, an article was published in the prestigious Scientific Reports journal by Nature, arguing that “AI holds the potential to carry out several major activities at much lower emission levels than can humans.” The piece argues that humans produce far greater CO2 emissions when doing writing or illustration work than AI Large Language Models. The article also notes that: “The freed human time may also incur new, unexpected environmental costs.” Advances in AI haven’t just led to humans being compared to machines but also being compared to animals. Late last year, according to The Guardian, BT’s Chief Innovation Officer, Harmeen Mehta ‘suggested workers whose jobs are threatened by AI accept their fate as “evolution,” comparing them to horses replaced by the car.’ Against this backdrop, one does wonder when we will inevitably see the rise of those who will argue for eugenics such that humans replace machines. This is nevertheless a stark reminder of how humans ultimately are behind killer computers. In a new book I authored called ‘ ,’ I have explored many catastrophic computer disasters. These disasters have included an aircraft entering ‘death dives’, fatal car crashes and lethal radiation doses. How to Protect Yourself from Killer Computers Recently, software reliability has been pushed to the forefront of the public conscience. March 2024 saw system failures, causing McDonald’s outlets in the UK, Australia, and Japan to go offline. Panama Bread in the US saw IT outages, as did the UK high-street giants Tesco, Sainsbury's, and Greggs. As several Boeing executives stood down from their jobs following the death of a whistleblower, it’s worth remembering how the first Boeing 737 MAX groundings began with a computer software problem. Previously unreported, it was also the case that March 2024 saw London police officers report chaos in jails and being unable to begin search warrant applications, as there was also an outage with the Metropolitan Police’s IT systems. The public inquiry into the UK Post Office’s Horizon IT Scandal is underway, a scandal where faulty accounting software resulted in miscarriages of justice, claiming around 700 victims and has been linked to four suicides. This included a pregnant mother being sent to jail. Engineers are now facing the consequences for being complicit in disasters; with FTX’s former Director of Engineering facing up to 75 years in prison, a VW engineer who was complicit in the emissions scandal having been sentenced to 40 months imprisonment despite co-operating with investigators and the architect of the Post Office Horizon IT system currently under investigation by UK police for perjury. In common across all these disasters, whilst the technical factors varied, I found a common theme of wrongdoing, retaliation, and cover-up. Issues were brushed under the carpet instead of addressed directly. For example, one engineering manager at Fujitsu, who built the software behind the Post Office scandal, told the public inquiry how he “was threatened with violence by an individual with a reputation for violence” during one of his early attempts to remedy the issues. This is an industry-wide problem. In November 2023, I led research that found that 53% of software engineers suspected wrongdoing at work, with 75% of software engineers in the UK having experienced retaliation the last time they reported it to their employers. This is a concern as computers do inevitably make mistakes as no software is perfect. Small things like a binary number being flipped (e.g., a “1” becoming a “0”) due to cosmic rays are enough to cause havoc in computer systems, particularly those that haven’t been designed with this risk in mind. There is, however, hope here. The research conducted in the new book finds that resilient systems can be built when humans are part of the system. In these , humans play a role in preventing disaster by raising the alarm and mitigating the issues. socio-technical systems For this to happen, humans must be free to raise the alarm to issues when they come across them. If the on-call engineers who keep our online services and critical national infrastructure running are not able to speak up and act to prevent disaster, these problems emerge. However, this applies to all software engineers and, indeed, everyone who is part of the software development process, including the customers. Killer computers are born in toxic cultures where engineers aren’t able to raise the alarm, and issues are brushed under the carpet. By making sure humans play a key role in the reliability of computer systems, we can help ensure technology serves society.

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